The normal frequency range for human hearing (sonic range) is roughly 20 to 20,000 hertz. Ultrasonic sound waves have frequencies above the frequency range of human hearing. Accordingly, any frequency above 20,000 hertz may be considered ultrasonic. Most industrial processes, including almost all sources of friction, create some ultrasonic noise. For example, leaks in pipes, machinery defects, and electrical arcing produce sonic or audible sound waves, as well as, ultrasonic sound waves.
In the past, handheld diagnostic instruments, such as ultrasonic “guns”, have utilized both sonic and ultrasonic sensors for monitoring machinery health. These older instruments provide a quick check of a machine's condition and do not typically perform extensive analysis. Often, these instruments allow a user to audibly listen to the machinery sound or vibration, and provide a method of measuring the magnitude of the sound or vibration. Heterodyning inaudible signals (i.e. ultrasonic signals) provides an audible representation of the signals in the sonic range, enabling a user to hear the signals.
An analog meter, bargraph, or digital display are used to indicate the vibration amplitude or magnitude. Some instruments may include peak, peak hold, averaging, and other signal conditioning functions to increase the possibility of a successful diagnosis. Other instruments output the vibration signal to an external instrument, such as an oscilloscope, data collector, or a Fourier Transform analyzer. Such practice, while sometimes necessary to make a likely diagnosis, is time consuming and requires a user to have some level of analysis skill.
Most of these prior art instruments rely heavily upon the observation, skill, and experience of the user to provide a diagnosis of a machine's health. Additionally, machinery faults can remain undetected when a fault is masked by background noise or when signals unrelated to the defect are present.
It has been found that certain machine faults reveal themselves in unique frequency ranges. Leak detection, for example, generally works well at an ultrasonic frequency of around 40 kHz. In rotating machinery, lubrication problems can be reliably detected at approximately 30 kHz. Mechanical bearing defects, especially those in the larger bearings found in industrial environments, are best detected in a frequency band of about 2–6 kHz. Some instruments provide quantitative measurements in selected frequency bands. This allows a skilled user to better diagnose and identify the type of fault that is occurring. However, the user of the instrument must still rely primarily on his skill level and judgment to identify the fault.
What is needed, therefore, is a device and a method which provides automated fault diagnosis of a system which overcomes the shortcomings associated with prior art instruments.